Infrastructure Engineer
Build and operate scalable data infrastructure, including partner data sharing, identity graph foundations, and governed batch and real-time platforms. The role requires 5+ years of data, distributed systems, infrastructure, or backend engineering experience and strong cloud and data-platform expertise.
About the job
Responsibilities
- Design, build, and operate scalable data infrastructure for high-volume ingestion, transformation, storage, and access.
- Architect and implement a secure, reliable, and governed partner data-sharing platform.
- Build foundational components of an identity graph connecting customer, account, transaction, partner, and behavioral data.
- Improve data quality, lineage, observability, reliability, governance, and access controls across pipelines and datasets.
- Partner with Data, Risk, Product, Engineering, Security, and Compliance teams to define platform capabilities.
- Build reusable abstractions, tooling, frameworks, APIs, and documentation for safe data creation, discovery, consumption, and sharing.
- Support batch and real-time data use cases while balancing latency, correctness, cost, and operational complexity.
- Address entity resolution, data freshness, schema evolution, privacy boundaries, and partner-specific data contracts.
- Improve systems through automation, monitoring, alerting, incident response, and capacity planning.
- Promote reproducible pipelines, clear ownership, robust testing, and operational excellence.
Requirements
- 5+ years of hands-on engineering experience building data platforms, distributed systems, infrastructure, or backend systems at scale.
- Experience designing and operating production data pipelines with modern processing frameworks and orchestration tools.
- Deep understanding of data modeling, data quality, schema management, lineage, observability, and governance.
- Experience with cloud data infrastructure, including object storage, warehouses, lakehouse architectures, streaming systems, and compute platforms.
- Ability to design systems meeting complex data access, privacy, security, and compliance requirements.
- Strong backend engineering fundamentals and proficiency in one or more of Python, Java, Scala, Go, or Kotlin.
- Experience building platforms or services for multiple internal customers.
- Strong systems thinking and ability to evaluate latency, consistency, reliability, scalability, cost, and developer experience trade-offs.
- Excellent analytical, problem-solving, communication, ownership, and collaboration skills.
- Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or equivalent practical experience.
Nice to Have
- Partner-facing or externally shared data platform experience, including access control, auditing, and contract management.
- Experience with identity resolution, entity matching, graph-based data systems, customer 360 platforms, or knowledge graphs.
- Experience in regulated environments such as fintech, banking, lending, payments, SOC, or PCI.
- Experience with Kafka, Flink, Spark Streaming, or similar real-time technologies.
- Experience with Snowflake, Databricks, dbt, Airflow, Dagster, Iceberg, Delta Lake, or similar modern data-stack tools.
- Familiarity with privacy-preserving data sharing, clean rooms, data contracts, consent management, or fine-grained authorization.
- Experience with observability, automated validation, backfills, incident response, and service-level objectives.
Compensation and Benefits
- $170,000–$230,000 annual compensation, plus equity.
- Flexible paid time off.
- Fully covered healthcare, including dependent coverage.
- Access to One Medical and an FSA.
- 20 weeks of paid parental leave for primary caregivers and 8 weeks for all new parents.
- Choice of configured work computer.
Skills
Python, Java, Scala, Go, Kotlin, Apache Kafka, Apache Flink, Spark, Snowflake, Databricks, dbt, Apache Airflow, Dagster, Apache Iceberg, Delta Lake
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